SoroushVahidi/scidocs huggingface dataset:
DENSER Cities: A System for Dense Efficient Reconstructions of Cities
(2016)

This paper is about the efficient generation of dense, colored models of city-scale environments from range data and in particular, stereo cameras. Better maps make for better understanding; better understanding leads to better robots, but this comes at a cost. The computational and memory requirements of large dense models can be prohibitive. We provide the theory and the system needed to create cityscale dense reconstructions. To do so, we apply a regularizer over a compressed 3D data structure while dealing with the complex boundary conditions this induces during the data-fusion stage. We show that only with these considerations can we swiftly create neat, large, “well behaved” reconstructions. We evaluate our system using the KITTI dataset and provide statistics for the metric errors in all surfaces created compared to those measured with 3D laser. Our regularizer reduces the median error by 40% in 3.4 km of dense reconstructions with a median accuracy of 6 cm. For subjective analysis, we provide a qualitative review of 6.1 km of our dense reconstructions in an attached video. These are the largest dense reconstructions from a single passive camera we are aware of in the literature. Video: https://youtu.be/FRmF7mH86EQ
Running on four legs as though they were one
(1986)

that run on one leg. The generalization uf these one-leg algorithms for control of machines with several legs is explored. The generalization is quite simple when multilegged systems run with gaits that use the support legs one at a time. For these gaits the ~ n e-l e g algorithms can be used b o control multilegged running. The cortcept of a virtual leg is introduced to further extend the approach to gaits that use the legs in pairs, such as the trot, the pace, and the bound. These quadruped running gaits map into gaits that use one virtual leg for support at a rime, for which the one-leg algorithms can provide control. This approach was used in laboratory experiments to control a quadruped machine that runs with a trotting gait. 1. ~N1RUI)IICTION UNNING is a form of legged locomotion characterized by travel at high speed and by periods of ballistic flight during which all feet leave the ground. The basic control task is to establish a pattern of leg and body motions that stabilizes the attitude and altitude of the body while propelling the body in the desired direction at the desired speed 121. The characteristics of high speed and ballistic flight suggest that dynamics and active stability are important to accomplishing this control task, and to getting a better general understanding of running. In recent work the aulhors used dynamic techniques to control an experimental one-legged machine that balances itself as it runs by hopping [ 3 , 41. The goal of these experiments was to focus on the dynamic aspects of locomo-tion, while avoiding the difficult task of coordinating the behavior of several legs. This paper addresses the task of leg coordination by starting with the algorithms that were used to control the one-legged hopping machine, and extending them to control a quadruped running machine. The general goal is to develop a set of locomotion principles that applies to the dynamic behavior of diverse legged systems-machines and animals alike-independent of the number of legs.
Fusion of IMU and Vision for Absolute Scale Estimation in Monocular SLAM
(2011)

The fusion of inertial and visual data is widely used to improve an object’s pose estimation. However, this type of fusion is rarely used to estimate further unknowns in the visual framework. In this paper we present and compare two different approaches to estimate the unknown scale parameter in a monocular SLAM framework. Directly linked to the scale is the estimation of the object’s absolute velocity and position in 3D. The first approach is a spline fitting task adapted from Jung and Taylor and the second is an extended Kalman filter. Both methods have been simulated offline on arbitrary camera paths to analyze their behavior and the quality of the resulting scale estimation. We then embedded an online multi rate extended Kalman filter in the Parallel Tracking and Mapping (PTAM) algorithm of Klein and Murray together with an inertial sensor. In this inertial / monocular SLAM framework, we show a real time, robust and fast converging scale estimation. Our approach does not depend on known patterns in the vision part nor a complex temporal synchronization between the visual and inertial sensor. The research leading to these results has received funding from the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement n. 231855 (sFly). Gabriel Nützi is currently a Master student at the ETH Zurich. Stephan Weiss is currently PhD student at the ETH Zurich. Davide Scaramuzza is currently senior researcher and team leader at the ETH Zurich. Roland Siegwart is full professor at the ETH Zurich and head of the Autonomous Systems Lab. G. Nützi · S. Weiss · D. Scaramuzza · R. Siegwart ETH Autonomous Systems Laboratory, 8092, Zurich, Switzerland, www.asl.ethz.ch E-mail: nuetzi@student.ethz.ch, stephan.weiss@mavt.ethz.ch, davide.scaramuzza@ieee.org, rsiegwart@ethz.ch 2
On Realistically Attacking Tor with Website Fingerprinting
(2016)

Website fingerprinting allows a local, passive observer monitoring a web-browsing client’s encrypted channel to determine her web activity. Previous attacks have shown that website fingerprinting could be a threat to anonymity networks such as Tor under laboratory conditions. However, there are significant differences between laboratory conditions and realistic conditions. First, the training data set is very similar to the testing data set under laboratory conditions, but the attacker may not be able to guarantee similarity realistically. Second, laboratory packet sequences correspond to a single page each, but for realistic packet sequences the split between pages is not obvious. Third, packet sequences may include noise, which may adversely affect website fingerprinting, but this effect has not been studied. In this paper, we tackle these three problems to bridge the gap between laboratory and realistic conditions for website fingerprinting. We show that we can maintain a fresh training set with minimal resources. We demonstrate several classification-based techniques that allow us to split full packet sequences effectively into sequences corresponding to a single page each. Although we were not able to remove noise effectively, we will show that it is difficult for users to generate sufficient background noise to disrupt website fingerprinting on Tor. With our techniques, we are able to build the first website fingerprinting system that can operate on packet sequences collected in the wild.
Low Precision Policy Distillation with Application to Low-Power, Real-time Sensation-Cognition-Action Loop with Neuromorphic Computing
(2018)

Low precision networks in the reinforcement learning (RL) setting are relatively unexplored because of the limitations of binary activations for function approximation. Here, in the discrete action ATARI domain, we demonstrate, for the first time, that low precision policy distillation from a high precision network provides a principled, practical way to train an RL agent. As an application, on 10 different ATARI games, we demonstrate real-time end-to-end game playing on lowpower neuromorphic hardware by converting a sequence of game frames into discrete actions.
Embodied Cognition is Not What you Think it is
(2013)

The most exciting hypothesis in cognitive science right now is the theory that cognition is embodied. Like all good ideas in cognitive science, however, embodiment immediately came to mean six different things. The most common definitions involve the straight-forward claim that "states of the body modify states of the mind." However, the implications of embodiment are actually much more radical than this. If cognition can span the brain, body, and the environment, then the "states of mind" of disembodied cognitive science won't exist to be modified. Cognition will instead be an extended system assembled from a broad array of resources. Taking embodiment seriously therefore requires both new methods and theory. Here we outline four key steps that research programs should follow in order to fully engage with the implications of embodiment. The first step is to conduct a task analysis, which characterizes from a first person perspective the specific task that a perceiving-acting cognitive agent is faced with. The second step is to identify the task-relevant resources the agent has access to in order to solve the task. These resources can span brain, body, and environment. The third step is to identify how the agent can assemble these resources into a system capable of solving the problem at hand. The last step is to test the agent's performance to confirm that agent is actually using the solution identified in step 3. We explore these steps in more detail with reference to two useful examples (the outfielder problem and the A-not-B error), and introduce how to apply this analysis to the thorny question of language use. Embodied cognition is more than we think it is, and we have the tools we need to realize its full potential.
Approximation Theory of the Mlp Model in Neural Networks
(1999)

In this survey we discuss various approximation-theoretic problems that arise in the multilayer feedforward perceptron (MLP) model in neural networks. The MLP model is one of the more popular and practical of the many neural network models. Mathematically it is also one of the simpler models. Nonetheless the mathematics of this model is not well understood, and many of these problems are approximation-theoretic in character. Most of the research we will discuss is of very recent vintage. We will report on what has been done and on various unanswered questions. We will not be presenting practical (algorithmic) methods. We will, however, be exploring the capabilities and limitations of this model. In the rst two sections we present a brief introduction and overview of neural networks and the multilayer feedforward perceptron model. In Section 3 we discuss in great detail the question of density. When does this model have the theoretical ability to approximate any reasonable function arbritrarily well? In Section 4 we present conditions for simultaneously approximating a function and its derivatives. Section 5 considers the interpolation capability of this model. In Section 6 we study upper and lower bounds on the order of approximation of this model. The material presented in Sections 3{6 treats the single hidden layer MLP model. In Section 7 we discuss some of the diierences that arise when considering more than one hidden layer. The lengthy list of references includes many papers not cited in the text, but relevant to the subject matter of this survey.
aBCD18 - An advanced 0.18um BCD technology for PMIC application
(2009)

We present a new advanced 0.18um BCD(Bipolar-CMOS-DMOS) technology with the key features being a 40V HV-MOS and an SSTC(Sidewall Selective Transistor Cell) type EEPROM as well as complimentary available analog devices such as a high gain BJT, 4fF/um2 MIM capacitor, and 10k Ω/sq. poly resistor. To reduce device area and enhance latch up immunity, a 15um depth deep trench isolation process has been developed, which will help to significantly reduce the chip size.
Comparison of Sparse Representation and Fourier Discriminant Methods : Damage Location Classification in Indirect Lab-scale Bridge Structural Health Monitoring
(2013)

This paper presents a novel method for interpreting data to improve the indirect structural health monitoring (SHM) of bridges. The research presented in the study is part of an ongoing study aimed at developing a novel SHM paradigm for the health assessment of bridges. In this paradigm, we envision the use of an instrumented vehicle that assesses a bridge’s dynamic characteristics while traveling across the bridge. These characteristics are then correlated to the health of the structure by means of advanced signal processing and pattern recognition approaches. In this paper, we present and compare two classification algorithms that locate the presence of damages at well-defined locations on the structure: sparse representation and the Fourier discriminant methods, and find that the sparse representation method provides superior classification accuracy.
Three control flow obfuscation methods for Java software
(2006)

Three novel control computation (control flow) obfuscation methods are described for protecting Java class files. They are basic block fission obfuscation, intersecting loop obfuscation and replacing goto obfuscation. The basic block fission obfuscation splits some chosen basic block(s) into more basic blocks, in which opaque predicates and goto instructions are inserted to make decompiling unsuccessful. The intersecting loop obfuscation intersects two loops and then adds this pattern into programs. The intersecting loop structure should not appear in a Java source program or a class file. The replacing goto obfuscation replaces goto instructions with conditional branch instructions. The newmethods were tested against 16 decompilers. The study also implemented multi-level exit obfuscation and single-level exit obfuscation for comparison. Both the intersecting loop obfuscation and the replacing goto obfuscation successfully defeated all the decompilers.
Increasing Brand Attractiveness and Sales through Social Media Comments on Public Displays - Evidence from a Field Experiment in the Retail Industry
(2012)

Retailers and brands are just starting to utilize online social media to support their businesses. Simultaneously, public displays are becoming ubiquitous in public places, raising the question about how these two technologies could be used together to attract new and existing customers as well as strengthen the relationship toward a focal brand. Accordingly, in a field experiment we displayed brandand product-related comments from the social network Facebook as pervasive advertising in small-space retail stores, known as kiosks. From interviews conducted with real customers during the experiment and the corresponding analysis of sales data we could conclude three findings. Showing social media comments resulted in (1) customers perceiving brands as more innovative and attractive, (2) a measurable, positive effect on sales on both the brand and the product in question and (3) customers wanting to see the comments of others, but not their own, creating a give-andtake paradox for using public displays to show social media comments.
Proposal Manipulation of 3 D Objects in Immersive Virtual Environments
(2015)

Interactions within virtual environments (VE) often require manipulation of 3D virtual objects. For this purpose, several research have been carried out focusing on mouse, touch and gestural input. While existing mid-air gestures in immersive VE (IVE) can offer natural manipulations, mimicking interactions with physical objects, they cannot achieve the same levels of precision attained with mouse-based applications for computer-aided design (CAD). Following prevailing trends in previous research, such as degrees-offreedom (DOF) separation, virtual widgets and scaled user motion, we intend to explore techniques for IVEs that combine the naturalness of mid-air gestures and the precision found in traditional CAD systems. In this document we survey and discuss the state-of-the-art in 3D object manipulation. With challenges identified, we present a research proposal and corresponding work plan.
Invariant Visual Object and Face Recognition: Neural and Computational Bases, and a Model, VisNet
(2012)

Neurophysiological evidence for invariant representations of objects and faces in the primate inferior temporal visual cortex is described. Then a computational approach to how invariant representations are formed in the brain is described that builds on the neurophysiology. A feature hierarchy model in which invariant representations can be built by self-organizing learning based on the temporal and spatial statistics of the visual input produced by objects as they transform in the world is described. VisNet can use temporal continuity in an associative synaptic learning rule with a short-term memory trace, and/or it can use spatial continuity in continuous spatial transformation learning which does not require a temporal trace. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate top-down feedback connections to model the control of attention by biased competition in, for example, spatial and object search tasks. The approach has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene. The approach has also been extended to provide, with an additional layer, for the development of representations of spatial scenes of the type found in the hippocampus.
Nerve entrapment syndromes as a cause of pain in the hip, groin and buttock.
(1999)

In sports medicine, chronic hip, groin and buttock pain is a common diagnostic problem. Because of the complex anatomy of this region and the many potential neurological causes for pain, few sports clinicians have a detailed understanding of this problem. This paper discusses the clinical aspects of nerve entrapment syndromes related to sport and takes a regional approach in order to provide a diagnostic framework for the general sports physician. The various neurological syndromes are discussed and the surgical management elaborated in detail. For some specific conditions, such as the so-called 'piriformis syndrome', the pathophysiological understanding has changed since the early descriptions and now this particular diagnosis is often ascribed to almost any cause of buttock and/or hamstring symptoms. We discuss the nature of the origin of local symptoms and note that the often described symptoms are more likely due to compression of structures other then the sciatic nerve. Furthermore, the role of piriformis hypertrophy or anatomical nerve variations in the genesis of this syndrome must be questioned. We suggest renaming this the 'deep gluteal syndrome' to account for all of the observed phenomena. As sports medicine continues to develop a scientific basis, the role of nerve entrapments as the basis for chronic symptomatology is undergoing a new understanding and clinicians need to be aware of the diagnostic possibilities and be able to advise patients accordingly on the basis of scientific fact not anecdotal fiction.
On the use of words and n-grams for Chinese information retrieval
(2000)

In the processing of Chinese documents and queries in information retrieval (IR), one has to identify the units that are used as indexes. Words and n-grams have been used as indexes in several previous studies, which showed that both kinds of indexes lead to comparable IR performances. In this study, we carry out more experiments on different ways to segment documents and queries, and to combine words with n-grams. Our experiments show that a combination of the longest-matching algorithm with single characters is the best choice.
Detecting topic evolution in scientific literature: how can citations help?
(2009)

Understanding how topics in scientific literature evolve is an interesting and important problem. Previous work simply models each paper as a bag of words and also considers the impact of authors. However, the impact of one document on another as captured by citations, one important inherent element in scientific literature, has not been considered. In this paper, we address the problem of understanding topic evolution by leveraging citations, and develop citation-aware approaches. We propose an iterative topic evolution learning framework by adapting the Latent Dirichlet Allocation model to the citation network and develop a novel inheritance topic model. We evaluate the effectiveness and efficiency of our approaches and compare with the state of the art approaches on a large collection of more than 650,000 research papers in the last 16 years and the citation network enabled by CiteSeerX. The results clearly show that citations can help to understand topic evolution better.
Optimization by Direct Search: New Perspectives on Some Classical and Modern Methods
(2003)

Direct search methods are best known as unconstrained optimization techniques that do not explicitly use derivatives. Direct search methods were formally proposed and widely applied in the 1960s but fell out of favor with the mathematical optimization community by the early 1970s because they lacked coherent mathematical analysis. Nonetheless, users remained loyal to these methods, most of which were easy to program, some of which were reliable. In the past fifteen years, these methods have seen a revival due, in part, to the appearance of mathematical analysis, as well as to interest in parallel and distributed computing. This review begins by briefly summarizing the history of direct search methods and considering the special properties of problems for which they are well suited. Our focus then turns to a broad class of methods for which we provide a unifying framework that lends itself to a variety of convergence results. The underlying principles allow generalization to handle bound constraints and linear constraints. We also discuss extensions to problems with nonlinear constraints.
On automatic differentiation
(1988)

During these last years, the environmental problems have acquired a growing place in our society. It becomes necessary to find a lasting way to the nuclear waste storage. The waste storage is in relation to the characteristics of wastes according to their activity and the life of the radionuclide. After many studies on the topic, led in particular by ANDRA, the storage in deep level is considered as the reference strategy for wastes with high or medium activity and long-lived. We have to make simulations of the radionucleide transport in underground in order to determine the impact of a possible propagation of radioelements. The modelling of the flow in porous media around the storage requires to know the physical parameters of the different geological layers. Those parameters (porosity and diffusion) are not directly accessible by measurements, hence we have to solve an inverse problem to recover them.